One of two permanent intelligence cores at Aonxi. ARIA finds capital. AROS finds revenue. Both learn from the same brain. Both compound forever.
ARIA finds investors, scores them by thesis fit, verifies every email, profiles their psychological defense mode, writes a message calibrated to bypass that defense, creates the campaign, and sends it.
Autonomously. The same system that finds revenue now finds capital.
First deployment — March 2026:
Investors contacted: General Catalyst, Bessemer, Antler,
Blume VC, Kae Capital + 14 more
Emails sent: 19
Bounces caught: 4 (before sending — domain reputation protected)
Raising: $250K pre-seed
Product: $199K collected, $0 raised, 40 customers
The product being used to raise money is being used to raise the money. Every investor who receives an ARIA email is watching it work before they reply.
VCs are MOTIVE_INFERENCE — awareness score 9/10.
They spend their careers evaluating pitches. They have read 10,000 cold emails. They decoded your intent before you finished the subject line.
Most founder emails look like this:
Hi Sarah — I'm really excited to share what we're building at Aonxi. I think there's a great opportunity here and would love to connect for a quick call.
Every word triggers a defense. Excited — detected. Great opportunity — detected. Quick call — detected. Email deleted before the second paragraph.
ARIA sends emails that look like this:
$199K collected. $8K peak day. $0.50/day to run. Zero sales reps. Code is public. You backed [company] — autonomous GTM at the SMB layer. This is that, built and verified. 20 minutes. No deck.
No "I". No pitch language. No excitement. Data, a specific signal, a specific ask.
That is PURE_DATA bypass for MOTIVE_INFERENCE defense.
Same 10 defense modes. Different population distribution. PKM Analyzer — try it live (free, no key needed).
| Investor type | Defense mode | Bypass | What changes |
|---|---|---|---|
| VC partner (ex-GTM) | MOTIVE_INFERENCE | PURE_DATA | Opens with a number, never "I'm excited to" |
| Operator angel | TACTIC_RECOGNITION | SIGNAL_HOOK | References their specific portfolio company |
| Technical investor | SOCIAL_PROOF_SKEPTICISM | CREDIBILITY_FIRST | Verifiable numbers only, no "trusted by" |
| First-time angel | AUTHORITY_DEFERENCE | PEER_PROOF | Names other angels who committed |
| Busy SMB operator | OVERLOAD_AVOIDANCE | ULTRA_SHORT | 60-word hard cap, specific calendar slot |
ARIA detects which one. ARIA writes for that one. Every time.
All defense profiles are cached in Airtable — shared across ARIA and AROS. A prospect analyzed by one agent is instantly available to the other.
Based on Friestad & Wright (1994) — 30 years of persuasion psychology.
Every investor ARIA contacts is recorded.
- Which thesis keywords converted
- Which defense mode each investor was running
- Which bypass strategy got the reply
- Which time of day a specific fund partner opens emails
- Which portfolio signal triggered the conversation
This pattern library compounds every raise. The next founder who uses ARIA gets the benefit of every raise that came before them.
aria.py CLI entry — 13 commands, one pipeline
aria_db.py SQLite dedup engine (source of truth)
apollo_client.py Investor finding + enrichment
millionverifier.py Email verification before send
investor_scorer.py Thesis fit scoring (Tier 1/2/3)
investor_researcher.py SerpAPI research
investor_writer.py Claude Haiku email generation (PKM applied)
instantly_client.py Campaign creation + send + tracking
airtable_sync.py Visual CRM dashboard sync
linkedin_prep.py HeyReach CSV for LinkedIn outreach
reply_processor.py Claude reply classification + HOT alerts
briefing.py Daily 7am pipeline email
One command:
python aria.py runFind → Score → Verify → Research → Profile → Write → Send → Track → Learn.
Stack: Claude Haiku / Apollo / Millionverifier / SerpAPI / Instantly / Airtable / SQLite
| Gen | Name | Status | What it adds |
|---|---|---|---|
| 1 | Pipeline | LIVE | Find → Score → Verify → Research → Profile → Write → Send |
| 2 | Learner | Week 4 | A/B testing, auto-adjust scoring from reply data |
| 3 | Researcher | Week 8 | Real-time portfolio moves, trigger-based outreach |
| 4 | Negotiator | Week 12 | Objection handling, warm intro path mapping |
| 5 | Autonomous | Week 16 | Zero human input, self-sourcing, self-qualifying |
| Command | What it does |
|---|---|
aria run |
Full pipeline: find → verify → score → research → write → send |
aria run --auto |
Same but skip preview — send all automatically |
aria status |
Pipeline dashboard |
aria replies |
Check Instantly for replies, classify, alert on HOT |
aria followup |
Day 5-8 follow-ups for non-responders |
aria linkedin |
Generate HeyReach CSV for LinkedIn outreach |
aria briefing |
Send daily pipeline email |
aria load FILE |
Import CSV manually |
aria verify |
Run Millionverifier on unverified emails |
aria score |
Score all unscored investors |
aria research N |
Research top N investors via SerpAPI |
aria write |
Write emails for top scored investors |
aria sync |
Sync to Airtable CRM dashboard |
git clone https://github.com/originaonxi/ARIA
cd ARIA
pip install -r requirements.txt
cp .env.example .env
# Add your keys to .env
python aria.py run| Repo | What it does |
|---|---|
| AROS | Finds revenue — the other intelligence core |
| PKM Analyzer | Defense profiling — try it live |
| VISION.md | The full Aonxi vision — AGI revenue layer for 400M businesses |
Built by Anmol Sam — origin@aonxi.com / originaonxi.github.io / aonxi.app